Acceleration of 2-D Multiplicative Regularized Contrast Source Inversion Algorithm Using Paralleled Computing Architecture

Abstract

Nonlinear inversion algorithms of electromagnetic data have been widely used. However, computational cost is still one of the bottlenecks for their applications. In this letter, we study an acceleration scheme for the multifrequency multiplicative regularized contrast source inversion algorithm using compute unified device architecture and graphic process unit (GPU). Numerical results show that the optimized algorithm on paralleled computing device outperforms the one on CPU processors with a significant reduction on computing time while keeping the same level of reconstruction quality. By using this algorithm, we successfully invert the microwave experimental data (2-D Fresnel dataset) in only a few minutes.